This chapter provides periodic insights into crime data for the space-time visualization of different crime patterns, highlights the spatial clustering patterns involved, and conducts a predictive analysis of crime trends perpetrated against women in West Bengal using relevant geostatistical modeling. The integration of statistical methods with Geographic Information System (GIS) tools is essential for a complete understanding of crime patterns and for the spatial modeling of crime data. Moran’s I is performed to highlight the spatial clustering patterns of crime against women in West Bengal. Autoregressive integrated moving average (ARIMA), a deep-learning model architecture, is implemented to forecast future crime trends with improved predictive accuracy. Identifying the most vulnerable districts with higher crime rates and predicting future crime trends have strong policy implications for endorsing space-based policing in crime-ridden zones.